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source("./tianfengRwrappers.R")

CA_dataset2 <- readRDS("./CA_dataset2.rds")
# CA_dataset2 <- RenameIdents(CA_dataset2,'EC' = 'Endothelial cell','FB' = 'Fibroblast')

umap图

小提琴图

vio <- violin_plot(c("MS4A1","PECAM1","FBLN1","CD68","TPSAB1","STMN1","NKG7","TAGLN","IL7R"), CA_dataset2) + 
  theme(axis.text.y = element_text(size = 18,colour = "black")) + scale_x_discrete(position = "right")

Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing scale.

热图 top30的marker，展示其中的部分

```r
Idents(CA_dataset2) <- CA_dataset2$Classification1
CA_dataset2_markers <- FindAllMarkers(CA_dataset2, logfc.threshold = 1, min.diff.pct = 0.3)
top30genes <- CA_dataset2_markers[CA_dataset2_markers$pct.1>0.7,] %>% group_by(cluster) %>% slice_max(n = 30, order_by = avg_logFC)

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```r
```r
library(ComplexHeatmap)
##提取标准化表达矩阵
mat <- GetAssayData(CA_dataset2, slot = \scale.data\)

gene_show <- c(\LYZ\,\CD68\,\SPP1\,\PECAM1\,\VWF\,\PLVAP\,\MYL9\,\TAGLN\,\ACTA2\,\DCN\,\APOD\,\FBLN1\,\CD69\,\CD79A\,\MS4A1\,\TPSAB1\,\TPSB2\,\NKG7\,\STMN1\,\CENPF\,\CPA3\,\IL7R\,\TRAC\)

##获得基因和细胞聚类信息
cluster_info <- sort(CA_dataset2$Classification1)
condition_info <- sort(CA_dataset2$conditions)
heatmapgenes <- intersect(top30genes$gene,rownames(mat))

##筛选矩阵
mat <- as.matrix(mat[heatmapgenes,names(cluster_info)])

#获得基因在热图中的位置信息
gene_pos <- match(gene_show, rownames(mat))
row_anno <- rowAnnotation(gene=anno_mark(at=gene_pos,labels = gene_show))

col <- colors_list
names(col) <- levels(cluster_info)
top_anno <- HeatmapAnnotation(cluster=anno_block(gp=gpar(fill=col),labels = levels(cluster_info),
 labels_gp = gpar(cex=1,col='black')))

library(circlize)
col_fun <-  colorRamp2(c(-2, 1, 4), c(\#1E90FF\, \white\, \#ff2121\))

svg(\CA_dataset2_markers.svg\,height = 6,width = 10)
Heatmap(mat, cluster_rows = FALSE, cluster_columns = FALSE, 
        show_column_names = FALSE, show_row_names = FALSE,
 column_split = cluster_info, top_annotation = top_anno,  
 column_title = NULL, right_annotation = row_anno, 
 heatmap_legend_param = list(
 title='Expression', title_position='leftcenter-rot'), col = col_fun)
dev.off()

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# 比例

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```r
ggsave("CAdataset2_prop.svg",device = svg, plot = prop_plot,width = 6,height = 5)

错误: Aesthetics must be either length 1 or the same as the data (18): fill
Run `rlang::last_error()` to see where the error occurred.

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